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Abstract Background The salience network (SN) is a transitory mediator between active and passive states of mind. Multiple cortical areas, including the opercular, insular, and cingulate cortices have been linked in this processing, though knowledge of network connectivity has been devoid of structural specificity. Objective The current study sought to create an anatomically specific connectivity model of the neural substrates involved in the salience network. Methods A literature search of PubMed and BrainMap Sleuth was conducted for resting‐state and task‐based fMRI studies relevant to the salience network according to PRISMA guidelines. Publicly available meta‐analytic software was utilized to extract relevant fMRI data for the creation of an activation likelihood estimation (ALE) map and relevant parcellations from the human connectome project overlapping with the ALE data were identified for inclusion in our SN model. DSI‐based fiber tractography was then performed on publicaly available data from healthy subjects to determine the structural connections between cortical parcellations comprising the network. Results Nine cortical regions were found to comprise the salience network: areas AVI (anterior ventral insula), MI (middle insula), FOP4 (frontal operculum 4), FOP5 (frontal operculum 5), a24pr (anterior 24 prime), a32pr (anterior 32 prime), p32pr (posterior 32 prime), and SCEF (supplementary and cingulate eye field), and 46. The frontal aslant tract was found to connect the opercular‐insular cluster to the middle cingulate clusters of the network, while mostly short U‐fibers connected adjacent nodes of the network. Conclusion Here we provide an anatomically specific connectivity model of the neural substrates involved in the salience network. These results may serve as an empiric basis for clinical translation in this region and for future study which seeks to expand our understanding of how specific neural substrates are involved in salience processing and guide subsequent human behavior.

Background: There are few treatments with limited efficacy for patients with disorders of consciousness (DoC), such as minimally conscious and persistent vegetative state (MCS and PVS).Objective: In this meta-analysis of individual patient data (IPD), we examine studies utilizing transcranial magnetic stimulation (TMS) as a treatment in DoC to determine patient and protocol-specific factors associated with improved outcomes.Methods: We conducted a systematic review of PubMed, Ovid Medline, and Clinicaltrials.gov through April 2020 using the following terms: “minimally conscious state,” or “persistent vegetative state,” or “unresponsive wakefulness syndrome,” or “disorders of consciousness” and “transcranial magnetic stimulation.” Studies utilizing TMS as an intervention and reporting individual pre- and post-TMS Coma Recovery Scale-Revised (CRS-R) scores and subscores were included. Studies utilizing diagnostic TMS were excluded. We performed a meta-analysis at two time points to generate a pooled estimate for absolute change in CRS-R Index, and performed a second meta-analysis to determine the treatment effect of TMS using data from sham-controlled crossover studies. A linear regression model was also created using significant predictors of absolute CRS-R index change.Results: The search yielded 118 papers, of which 10 papers with 90 patients were included. Patients demonstrated a mean pooled absolute change in CRS-R Index of 2.74 (95% CI, 0.62–4.85) after one session of TMS and 5.88 (95% CI, 3.68–8.07) at last post-TMS CRS-R assessment. The standardized mean difference between real rTMS and sham was 2.82 (95% CI, −1.50 to 7.14), favoring rTMS. The linear regression model showed that patients had significantly greater CRS-R index changes if they were in MCS, had an etiology of stroke or intracranial hemorrhage, received 10 or more sessions of TMS, or if TMS was initiated within 3 months from injury.Conclusions: TMS may improve outcomes in MCS and PVS. Further evaluation with randomized, clinical trials is necessary to determine its efficacy in this patient population.

Abstract Introduction The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task‐based fMRI studies, we built a neuroanatomical model of this network. Methods One hundred and fifty‐five task‐based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network. Results The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model. Conclusions We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application.

Abstract Background The default mode network (DMN) is an important mediator of passive states of mind. Multiple cortical areas, such as the anterior cingulate cortex, posterior cingulate cortex, and lateral parietal lobe, have been linked in this processing, though knowledge of network connectivity had limited tractographic specificity. Methods Using resting‐state fMRI studies related to the DMN, we generated an activation likelihood estimation (ALE). We built a tractographical model of this network based on the cortical parcellation scheme previously published under the Human Connectome Project. DSI‐based fiber tractography was performed to determine the structural connections between cortical parcellations comprising the network. Results Seventeen cortical regions were found to be part of the DMN: 10r, 31a, 31pd, 31pv, a24, d23ab, IP1, p32, POS1, POS2, RSC, PFm, PGi, PGs, s32, TPOJ3, and v23ab. These regions showed consistent interconnections between adjacent parcellations, and the cingulum was found to connect the anterior and posterior cingulate clusters within the network. Conclusions We present a preliminary anatomic model of the default mode network. Further studies may refine this model with the ultimate goal of clinical application.

Abstract Introduction The dorsal attention network (DAN) is an important mediator of goal‐directed attentional processing. Multiple cortical areas, such as the frontal eye fields, intraparietal sulcus, superior parietal lobule, and visual cortex, have been linked in this processing. However, knowledge of network connectivity has been devoid of structural specificity. Methods Using attention‐related task‐based fMRI studies, an anatomic likelihood estimation (ALE) of the DAN was generated. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co‐registered onto the ALE in MNI coordinate space and visually assessed for inclusion in the network. DSI‐based fiber tractography was performed to determine the structural connections between relevant cortical areas comprising the network. Results Twelve cortical regions were found to be part of the DAN: 6a, 7AM, 7PC, AIP, FEF, LIPd, LIPv, MST, MT, PH, V4t, VIP. All regions demonstrated consistent u‐shaped interconnections between adjacent parcellations. The superior longitudinal fasciculus connects the frontal, parietal, and occipital areas of the network. Conclusions We present a tractographic model of the DAN. This model comprises parcellations within the frontal, parietal, and occipital cortices principally linked through the superior longitudinal fasciculus. Future studies may refine this model with the ultimate goal of clinical application.

Abstract Background The use of intrathecal antibiotic therapy for the treatment of ventriculitis and/or meningitis has demonstrated efficacy especially when sterilization of the cerebrospinal fluid is not possible with intravenous antibiotics alone. Case Description We describe the successful treatment of Enterococcus faecalis ventriculitis utilizing intrathecal linezolid in a 32-year-old female patient with severe allergy to vancomycin, prohibitive bacterial susceptibilities, and failure of previous attempts to sterilize the cerebrospinal fluid despite multimodal treatment. Conclusion Intrathecal linezolid is a useful treatment in the setting of multidrug-resistant bacterial ventriculitis. We present a useful dosing regimen for the administration of intrathecal linezolid.

Abstract Fractures of the anterior skull base may occur in gunshot victims and can result in traumatic cerebrospinal fluid (CSF) leak. Less commonly, CSF leaks occur days or even weeks after the trauma occurred. Here, we present the case of a 21-year-old man with a delayed-onset, traumatic CSF leak secondary to a missile injury that left a bullet fragment in the Rosenmuller fossa. The patient was treated successfully with endoscopic, endonasal extraction of the bullet, and repair with a nasal septal flap. Foreign bodies lodged in Rosenmuller fossa can be successfully treated with endoscopic skull base surgery.